Acknowledgments |
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xvii | |
Introduction |
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1 | (27) |
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The ET Interview: Professor Clive Granger |
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28 | (57) |
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PART ONE: SPECTRAL ANALYSIS |
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Spectral Analysis of New York Stock Market Prices |
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85 | (21) |
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The Typical Spectral Shape of an Economic Variable |
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106 | (15) |
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PART TWO: SEASONALITY |
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Seasonality: Causation, Interpretation and Implications |
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121 | (26) |
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Is Seasonal Adjustment a Linear or Nonlinear Data-Filtering Process? |
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147 | (30) |
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PART THREE: NONLINEARITY |
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Non-Linear Time Series Modeling |
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177 | (11) |
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Using the Correlation Exponent to Decide Whether an Economic Series is Chaotic |
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188 | (20) |
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Testing for Neglected Nonlinearity in Time Series Models: A Comparison of Neural Network Methods and Alternative Tests |
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208 | (22) |
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Modeling Nonlinear Relationships Between Extended-Memory Variables |
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230 | (17) |
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Semiparametric Estimates of the Relation Between Weather and Electricity Sales |
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247 | (26) |
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PART FOUR: METHODOLOGY |
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Time Series Modeling and Interpretation |
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273 | (16) |
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On the Invertibility of Time Series Models |
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289 | (7) |
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Near Normality and Some Econometric Models |
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296 | (6) |
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The Time Series Approach to Econometric Model Building |
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302 | (15) |
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Comments on the Evaluation of Policy Models |
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317 | (19) |
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Implications of Aggregation with Common Factors |
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336 | (19) |
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PART FIVE: FORECASTING |
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Estimating the Probability of Flooding on a Tidal River |
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355 | (11) |
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Prediction with a Generalized Cost of Error Function |
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366 | (9) |
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Some Comments on the Evaluation of Economic Forecasts |
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375 | (16) |
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The Combination of Forecasts |
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391 | (20) |
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Invited Review: Combining Forecasts - Twenty Years Later |
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411 | (9) |
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The Combination of Forecasts Using Changing Weights |
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420 | (16) |
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Forecasting Transformed Series |
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436 | (21) |
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457 | (15) |
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Can We Improve the Perceived Quality of Economic Forecasts? |
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472 | (25) |
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Short-Run Forecasts of Electricity Loads and Peaks |
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497 | (20) |
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Index |
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Acknowledgments |
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xiii | |
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xvii | |
Introduction |
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1 | (30) |
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PART ONE: CAUSALITY |
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Investigating Causal Relations by Econometric Models and Cross-Spectral Methods |
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31 | (17) |
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Testing for Causality: A Personal Viewpoint |
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48 | (23) |
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Some Recent Developments in a Concept of Causality |
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71 | (13) |
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Advertising and Aggregate Consumption: An Analysis of Causality |
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84 | (25) |
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PART TWO: INTEGRATION AND COINTEGRATION |
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Spurious Regression in Econometrics |
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109 | (10) |
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Some Properties of Time Series Data and Their Use in Econometric Model Specification |
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119 | (10) |
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Time Series Analysis of Error Correction Models |
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129 | (16) |
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Co-Integration and Error-Correction: Representation, Estimation, and Testing |
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145 | (28) |
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Developments in the Study of Cointegrated Economic Variables |
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173 | (16) |
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Seasonal Integration and Cointegration |
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189 | (23) |
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A Cointegration Analysis of Treasury Bill Yields |
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212 | (20) |
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Estimation of Common Long Memory Components in Cointegrated Systems |
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232 | (22) |
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Separation in Cointegrated Systems and Persistent-Transitory Decompositions |
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254 | (15) |
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Nonlinear Transformations of Integrated Time Series |
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269 | (17) |
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Long Memory Series with Attractors |
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286 | (16) |
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Further Developments in the Study of Cointegrated Variables |
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302 | (19) |
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PART THREE: LONG MEMORY |
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An Introduction to Long-Memory Time Series Models and Fractional Differencing |
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321 | (17) |
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Long Memory Relationships and the Aggregation of Dynamic Models |
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338 | (11) |
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A Long Memory Property of Stock Market Returns and a New Model |
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349 | (24) |
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Index |
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373 | |